Several Global Navigation Satellite System (GNSS) applications, such as safety critical applications, require that a GNSS receiver monitor the integrity of the GNSS receiver's computed solution. The integrity of a computed solution is the level of trust that can be placed in the correctness of the computed solution. Monitoring the integrity of a computed solution protects users from position errors that arise from bad geometries, satellite faults, etc. that are not yet identified by the system ground monitoring network.
Current integrity monitoring schemes, such as Receiver Autonomous Integrity Monitoring (RAIM), determine whether there is a fault in a satellite measurement by examining the consistency of a set of redundant measurements. One way to do this is by using the solution separation method. The solution separation method for RAIM is based on computing the difference between a “full-solution” navigation solution that is rendered using all visible satellites (including a quantity of N visible satellites) and a set of navigation “sub-solutions” that are each rendered using a quantity of N−1 visible satellites. In computing the set of navigation sub-solutions, RAIM assumes only one satellite fault at a time. However, with the introduction of new Global Navigation Satellite System (GNSS) constellations (such as Galileo, BeiDou, etc.) and the continuing use of existing GNSS constellations (such as Global Positioning System (GPS), GLONASS, etc.), it is more likely that there could be multiple simultaneous satellite faults at a given time. Furthermore, entire constellation faults will also need to be considered by future integrity monitoring schemes.
In response to the likelihood of more than one fault occurring at the same time, Advanced Receiver Autonomous Integrity Monitoring (ARAIM) was developed. ARAIM is based on the solution separation method but it was modified to include multiple faults and constellation faults. For each fault that needs to be monitored, a navigation sub-solution that does not include the fault-associated measurements is created. For example, if dual faults (two simultaneous single faults) need to be monitored then a set of sub-solutions based on removing all possible combinations of 2 satellites needs to be created. Increasing the number of visible satellites and higher probabilities of simultaneous faults (as expected from new constellations), however, can dramatically increase the number of sub-solutions that need to be created. This, in turn, will have a large impact on the computational demands of the algorithm resulting in more expensive chips.